Genomic selection is an important tool to introduce feed efficiency into dairy cattle breeding. The goals of the current research are to estimate genomic breeding values of residual feed intake (RFI) and to assess the prediction reliability for RFI in the US Holstein population. The RFI data were collected from 4,823 lactations of 3,947 Holstein cows in 9 research herds in the United States, and were pre-adjusted to remove phenotypic correlations with milk energy, metabolic body weight, body weight change, and for several environmental effects. In the current analyses, genomic predicted transmitting abilities of milk energy and of body weight composite were included into the RFI model to further remove the genetic correlations that remained between RFI and these energy sinks. In the first part of the analyses, a national genomic evaluation for RFI was conducted for all the Holsteins in the national database using a standard multi-step genomic evaluation method and 60,671 SNP list. In the second part of the study, a single-step genomic prediction method was applied to estimate genomic breeding values of RFI for all cows with phenotypes, 5,252 elite young bulls, 4,029 young heifers, as well as their ancestors in the pedigree, using a high-density genotype chip. Theoretical prediction reliabilities were calculated for all the studied animals in the single-step genomic prediction by direct inversion of the mixed model equations. In the results, breeding values were estimated for 1.6 million genotyped Holsteins and 60 million ungenotyped Holsteins, The genomic predicted transmitting ability correlations between RFI and other traits in the index (e.g., fertility) are generally low, indicating minor correlated responses on other index traits when selecting for RFI. Genomic prediction reliabilities for RFI averaged 34% for all phenotyped animals and 13% for all 1.6 million genotyped animals. Including genomic information increased the prediction reliabilities for RFI compared with using only pedigree information. All bulls had low reliabilities, and averaged to only 16% for the top 100 net merit progeny-tested bulls. Analyses using single-step genomic prediction and high-density genotypes gave similar results to those obtained from the national evaluation. The average theoretical reliability for RFI was 18% among the elite young bulls under 5 yr old, being lower in the younger generations of elite bulls compared with older bulls. To conclude, the size of the reference population and its relationship to the predicted population remain as the limiting factors in the genomic prediction for RFI. Continued collection of feed intake data is necessary so that reliabilities can be maintained due to close relationships of phenotyped animals with breeding stock. Considering the currently low prediction reliability and high cost of data collection, focusing RFI data collection on relatives of elite bulls that will have the greatest genetic contribution to the next generation will give more gains and profit.

中文翻译：

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美国荷斯坦奶牛剩余饲料摄入量的基因组预测。

基因组选择是将饲料效率引入奶牛育种的重要工具。当前研究的目的是估计残留饲料摄入量（RFI）的基因组育种值，并评估美国荷斯坦牛种群RFI的预测可靠性。RFI数据是从美国9个研究牛群的3,947头荷斯坦奶牛的4,823次泌乳中收集的，并且经过了预先调整，以消除与牛奶能量，代谢体重，体重变化以及多种环境影响的表型相关性。在当前的分析中，RFI模型包括了牛奶能量和体重复合物的基因组预测传递能力，以进一步消除RFI与这些能量汇之间的遗传相关性。在分析的第一部分，使用标准的多步基因组评估方法和60,671个SNP清单，对国家数据库中的所有荷斯坦牛进行了RFI的国家基因组评估。在研究的第二部分中，采用单步基因组预测方法来估算所有表型母牛，5,252头幼小公牛，4,029头小母牛及其谱系中的祖先的RFI的基因组育种值，使用高密度基因型芯片。通过对混合模型方程式进行直接反演，在单步基因组预测中计算了所有研究动物的理论预测可靠性。在结果中，估计了160万个基因型Holsteins和6000万个非基因型Holsteins的育种价值。该基因组预测了RFI和该指数中其他特征之间的传递能力相关性（例如，生育率通常较低），表明在选择RFI时对其他指标性状的反应较小。对于所有表型动物，RFI的基因组预测可靠性平均为34％，对于所有160万基因型动物，平均为13％。与仅使用谱系信息相比，包含基因组信息可提高RFI的预测可靠性。所有公牛的可靠性都较低，在前100名经过优异成绩的纯净后代测试的公牛中，平均水平仅为16％。使用单步基因组预测和高密度基因型进行的分析与从国家评估中获得的结果相似。在5岁以下的精英年轻公牛中，RFI的平均理论可靠性为18％，与年长的公牛相比，在年轻一代的精英公牛中较低。最后，参考种群的大小及其与预测种群的关系仍然是RFI基因组预测中的限制因素。必须继续收集饲料摄入量数据，以便由于表型动物与种畜的密切关系而可以保持可靠性。考虑到当前预测可靠性低和数据收集成本高的问题，将RFI数据收集重点放在对下一代遗传贡献最大的精英公牛的亲属中，将带来更多的收益和利润。